Remote Data Annotation Jobs in Denver

Rex.zone; Denver (CO); Remote; USD 42,000 - 54,000; Full time

Job summary

Rex.zone is seeking remote data annotators to join our Denver-based program supporting AI systems and LLM training pipelines. You will label data for NLP tasks, perform RLHF-style ranking, evaluate prompts, and contribute to content safety labeling while following strict guidelines.

This is a full-time remote role with US-based candidates welcome; you will work with web-based annotation tools, adhere to confidential data handling, and help drive quality through rigorous self- and peer reviews.

Qualifications

• Mid-Senior experience in data annotation, labeling, QA review, or AI/ML evaluation workflows.
• Strong written communication for rationales and guideline interpretations.
• Ability to follow rubrics with high consistency and quality standards.
• Comfort with web-based annotation tools and task tracking.
• Understanding of LLM training concepts (supervised fine-tuning data, RLHF, evaluation sets).

Responsibilities

• Perform data labeling for NLP tasks including named entity recognition, sentiment, intent, and taxonomy-based classification.
• Complete RLHF-style ranking and preference labeling to support LLM evaluation and alignment.
• Run prompt evaluation and response grading for accuracy, helpfulness, policy compliance, and reasoning quality.
• Execute content safety labeling using client rubrics (hate/harassment, self-harm, sexual content, violence).
• Annotate computer vision data when needed (bounding boxes, polygons, keypoints, segmentation masks).
• Apply annotation guidelines compliance, flag ambiguous items, and document edge cases.
• Conduct QA evaluation (self-check and peer review), track error types, and drive quality improvements.
• Maintain secure handling of sensitive data and adhere to confidentiality and platform policies.

Job description

Remote Data Annotation Jobs in Denver (US-Remote) Join Rex.zone to deliver high-accuracy labeled datasets and evaluation judgments used to build and improve AI systems and large language model (LLM) training pipelines. Work includes data labeling, RLHF preference ranking, prompt evaluation, QA evaluation, named entity recognition, computer vision annotation, and content safety labeling while following strict annotation guidelines compliance.

Key Responsibilities

• Perform data labeling for NLP tasks such as named entity recognition, sentiment, intent, and taxonomy-based classification
• Complete RLHF-style ranking and preference labeling to support LLM evaluation and alignment
• Run prompt evaluation and response grading for accuracy, helpfulness, policy compliance, and reasoning quality
• Execute content safety labeling using client rubrics (hate/harassment, self-harm, sexual content, violence)
• Annotate computer vision data when needed (bounding boxes, polygons, keypoints, segmentation masks)
• Apply annotation guidelines compliance, flag ambiguous items, and document edge cases
• Conduct QA evaluation (self-check and peer review), track error types, and drive quality improvements
• Maintain secure handling of sensitive data and adhere to confidentiality and platform policies

Required Qualifications

• Mid-Senior experience in data annotation, data labeling, QA review, or AI/ML evaluation workflows
• Strong written communication for rationales and guideline interpretations
• Ability to follow detailed rubrics with high consistency and quality standards
• Comfort working with web-based annotation tools and task tracking
• Understanding of LLM training concepts (supervised fine-tuning data, RLHF, evaluation sets)

Work Location and Schedule

Remote Type: Remote (Denver-based candidates welcomed; work performed remotely within the US). Employment Type: Full-time with sustained throughput and quality expectations.